Family Policy Scores by Country

Bar Horizontal Ordered

Photo by Nathan Dumlao on Unsplash

Don’t call the world dirty because you forgot to clean your glasses…
— Aaron Hill

Ingest

# Load data
df = read.csv("archetypes/family-policy-scores-by-country/family-policy-scores-by-country.csv", header = TRUE, stringsAsFactors = TRUE)
df

Plot the chart

Chart will plot as the original index in the dataframe

theme_opts <- theme(
    plot.margin = margin(.25, 1, .25, .25, "cm"),
    plot.background = element_blank(),
    panel.background = element_blank(),
    legend.position = "none",
    axis.title.x=element_blank(),
    axis.title.y=element_blank(),
    axis.ticks.y=element_blank(),
    axis.ticks.x=element_blank(),
    axis.text.x=element_blank(),
    strip.placement = "outside",                      # Place facet labels outside x axis labels.
    strip.background = element_rect(fill = "white"),  # Make facet label background white.
    axis.title = element_blank()                     # Remove x and y axis titles.
)

# Make the plot
v1 <- ggplot(df, aes(x=Family.Integration.Policy.Average.Scores, y=Country)) + 
  geom_bar(stat="identity", fill="#88b88a") +
  # scale_y_discrete(limits=c("Almond milk", "Oat milk", "Soy milk", "Rice milk","Cow's milk")) +
  #scale_fill_manual(values=c("Carbon Emissions (kg CO2eq)" = "#364e5d", "Land Use (m2)" = "#597e4e", "Water Use (L)" = "#587f89")) +
  #scale_color_manual(values=c("white" = "#ffffff", "black" = "#000000")) +
  coord_cartesian(clip="off") +
  labs(title = "FAMILY INTEGRATION POLICY AVERAGE SCORES BY COUNTRY, 2014") +
  theme_opts

# Print the plot
girafe(ggobj = v1, width_svg = 720/72, height_svg = 1280/72,
       options = list(opts_sizing(rescale = TRUE, width = 1.0)))

Rank From Highest to Lowest

As it is a horizontal Bar Chart, we reorder the y-axis.

Note: In the case of vertical Bar Charts, we will reorder the x-axis.

# Make the plot
v2 <- ggplot(df, aes(x=Family.Integration.Policy.Average.Scores, y=reorder(Country,Family.Integration.Policy.Average.Scores))) + 
  geom_bar(stat="identity", fill="#88b88a") +
  # scale_y_discrete(limits=c("Almond milk", "Oat milk", "Soy milk", "Rice milk","Cow's milk")) +
  #scale_fill_manual(values=c("Carbon Emissions (kg CO2eq)" = "#364e5d", "Land Use (m2)" = "#597e4e", "Water Use (L)" = "#587f89")) +
  #scale_color_manual(values=c("white" = "#ffffff", "black" = "#000000")) +
  coord_cartesian(clip="off") +
  labs(title = "FAMILY INTEGRATION POLICY AVERAGE SCORES BY COUNTRY, 2014") +
  theme_opts

# Print the plot
girafe(ggobj = v2, width_svg = 720/72, height_svg = 1280/72,
       options = list(opts_sizing(rescale = TRUE, width = 1.0)))

Rank from Lowest to Highest

The only change is putting a “-” sign infront of the axis we’re reordering.

# Make the plot
v3 <- ggplot(df, aes(x=Family.Integration.Policy.Average.Scores, y=reorder(Country,-Family.Integration.Policy.Average.Scores))) + 
  geom_bar(stat="identity", fill="#88b88a") +
  # scale_y_discrete(limits=c("Almond milk", "Oat milk", "Soy milk", "Rice milk","Cow's milk")) +
  #scale_fill_manual(values=c("Carbon Emissions (kg CO2eq)" = "#364e5d", "Land Use (m2)" = "#597e4e", "Water Use (L)" = "#587f89")) +
  #scale_color_manual(values=c("white" = "#ffffff", "black" = "#000000")) +
  coord_cartesian(clip="off") +
  labs(title = "FAMILY INTEGRATION POLICY AVERAGE SCORES BY COUNTRY, 2014") +
  theme_opts

# Print the plot
girafe(ggobj = v3, width_svg = 720/72, height_svg = 1280/72,
       options = list(opts_sizing(rescale = TRUE, width = 1.0)))

# As reusable function

make_hbar <- function(df, x_field, y_field, fill_str, title_str) {

x_var <- c(x_field)
y_var <- c(y_field)

ggplot(df, aes(x=get(x_var), y=get(y_var))) + 
  geom_bar(stat="identity", fill=fill_str) +
  coord_cartesian(clip="off") +
  labs(title = title_str) +
  theme_opts

}

References

Narrative and Data Source, United Nations GO